Geraint Wiggins
Geraint Wiggins
Professor of Computational Creativity, Vrije Universiteit Brussel / Queen Mary University of London
Verified email at vub.ac.be
Title
Cited by
Cited by
Year
Computational creativity: The final frontier?
S Colton, GA Wiggins
Ecai 12, 21-26, 2012
3112012
A preliminary framework for description, analysis and comparison of creative systems
GA Wiggins
Knowledge-Based Systems 19 (7), 449-458, 2006
3072006
Expectation in melody: The influence of context and learning
MT Pearce, GA Wiggins
Music Perception 23 (5), 377-405, 2006
2702006
AI methods for algorithmic composition: A survey, a critical view and future prospects
G Papadopoulos, G Wiggins
AISB Symposium on Musical Creativity 124, 110-117, 1999
2631999
Algorithms for discovering repeated patterns in multidimensional representations of polyphonic music
D Meredith, K Lemström, GA Wiggins
Journal of New Music Research 31 (4), 321-345, 2002
2162002
Unsupervised statistical learning underpins computational, behavioural, and neural manifestations of musical expectation
MT Pearce, MH Ruiz, S Kapasi, GA Wiggins, J Bhattacharya
NeuroImage 50 (1), 302-313, 2010
1972010
Searching for computational creativity
GA Wiggins
New Generation Computing 24 (3), 209-222, 2006
1742006
Musical creativity: multidisciplinary research in theory and practice
I Delège, GA Wiggins
Psychology Press, 2006
1542006
Auditory expectation: the information dynamics of music perception and cognition
MT Pearce, GA Wiggins
Topics in cognitive science 4 (4), 625-652, 2012
1492012
Improved methods for statistical modelling of monophonic music
M Pearce, G Wiggins
Journal of New Music Research 33 (4), 367-385, 2004
1392004
Evolutionary methods for musical composition
G Wiggins, G Papadopoulos, S Phon-Amnuaisuk, A Tuson
ICANNGA, 1998
1381998
Probabilistic models of expectation violation predict psychophysiological emotional responses to live concert music
H Egermann, MT Pearce, GA Wiggins, S McAdams
Cognitive, Affective, & Behavioral Neuroscience 13 (3), 533-553, 2013
1212013
Statistical learning of harmonic movement
D Ponsford, G Wiggins, C Mellish
Journal of New Music Research 28 (2), 150-177, 1999
1161999
A framework for the evaluation of music representation systems
G Wiggins, E Miranda, A Smaill, M Harris
Computer Music Journal 17 (3), 31-42, 1993
1151993
A genetic algorithm for the generation of jazz melodies
G Wiggins, G Papadopoulos
Proceedings of the Finnish Conference on Artificial Intelligence (STeP’98 …, 1998
114*1998
Towards a framework for the evaluation of machine compositions
M Pearce, G Wiggins
Proceedings of the AISB’01 Symposium on Artificial Intelligence and …, 2001
1032001
Motivations and methodologies for automation of the compositional process
M Pearce, D Meredith, G Wiggins
Musicae Scientiae 6 (2), 119-147, 2002
942002
The four-part harmonisation problem: a comparison between genetic algorithms and a rule-based system
S Phon-Amnuaisuk, G Wiggins
Proceedings of the AISB’99 Symposium on Musical Creativity, 28-34, 1999
921999
Converging on the divergent: The history (and future) of the international joint workshops in computational creativity
A Cardoso, T Veale, GA Wiggins
AI magazine 30 (3), 15-15, 2009
902009
The role of expectation and probabilistic learning in auditory boundary perception: A model comparison
MT Pearce, D Müllensiefen, GA Wiggins
Perception 39 (10), 1367-1391, 2010
892010
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